The molecular analysis of the signal transduction pathways driving uncontrolled growth in tumor cells will have a dramatic impact upon cancer biology and patient care. New technologies such as those to identify the genome and proteome of cells hold great promise. However these methods do not provide direct measurements of the activity of molecules involved in signal transduction. Ultimately it is the activation state of molecules such as enzymes that control cell behavior, for example, fueling the growth of tumor cells. A new technology and biochemical assay, the Laser Micropipet System (LMS), has the potential to perform simultaneous biochemical analysis of the activation state of multiple signal transducing enzymes within a single cell. Such data will enable misregulated signaling of tumor cells to be assessed in both linear signaling pathways and in interconnected networks of signaling proteins. The goal of this proposal is to apply the LMS to the Ras signaling cascades which are of immense importance in both the basic and clinical investigation of cancer. An interdisciplinary team with strengths in analytical chemistry, cancer biology, and organic chemistry has been assembled. The research will draw on methods from analytical chemistry to analyze, separate, and detect kinase substrates from single cells. The strengths of combinatorial chemistry and synthetic organic chemistry will be brought to bear on the development of new kinase substrates to be used as specific reporters of Ras-regulated kinase activation. Molecularly engineered tumor cell lines in which individual proteins have been selectively mutated will be used to demonstrate the capabilities of the LMS in measuring the activation of kinases in the Ras-regulated signaling cascades. Finally, a hypothesis of intense interest to cancer research will be addressed with this newly developed and expanded single-cell biochemical assay system. The successful completion of this work will provide a new and powerful tool for basic research, drug discovery and screening, cancer classification, and potentially clinical decision making.
